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        Note that additional data was saved in multiqc_data when this report was generated.


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        If you use plots from MultiQC in a publication or presentation, please cite:

        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411

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        About MultiQC

        This report was generated using MultiQC, version 1.25.2 (b317290)

        You can see a YouTube video describing how to use MultiQC reports here: https://youtu.be/qPbIlO_KWN0

        For more information about MultiQC, including other videos and extensive documentation, please visit http://multiqc.info

        You can report bugs, suggest improvements and find the source code for MultiQC on GitHub: https://github.com/MultiQC/MultiQC

        MultiQC is published in Bioinformatics:

        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411

        A modular tool to aggregate results from bioinformatics analyses across many samples into a single report.


        Summary Tables

        BAM Header Info

        Basic metadata extracted from the BAM header.

        Showing 0/1 rows and 5/5 columns.
        Sample NameVersionSort OrderPlatformGenome Assembly IdentifierTools
        HG00096
        1.0
        coordinate
        ILLUMINA
        N/A
        GenomeAnalysisTK | bam_calculate_bq | bam_count_covariates | bam_mark_duplicates | bam_merge | bam_merge.1 | bam_realignment_around_known_indels | bam_recalibrate_quality_scores | bwa | bwa_aln_fastq | bwa_index | bwa_sam | gatk_target_interval_creator | picard | sam_to_fixed_bam | samtools

        Genome Results Summary

        General information from the BAM file.

        Showing 0/1 rows and 15/15 columns.
        Sample NameFile nameNumber of readsNumber of mapped readsNumber of mapped paired reads (both in pair)Number of mapped paired reads (singletons)Median insert sizeMean mapping quality% GCGeneral error rateMean coverageStd coverage% Duplicated reads% ChimerasPF Q30 basesTotal bases
        HG00096
        HG00096.chrom11.ILLUMINA.bwa.GBR.low_coverage.20120522.bam
        6412020
        6396581
        6358321
        15439
        182
        2.1
        40.9
        0.0
        0.2
        1.1
        1.4
        0.2
        567431842
        641202000

        Median Coverage Across Reference

        This plot displays sequencing coverage across chromosomes, summarized as the median coverage within non-overlapping 3 Mb windows. It helps identify regions with unusually high or low coverage, which may reflect technical biases, duplications, or low-complexity regions.


        Mapping Quality Distribution

        This plot shows the number of genomic positions for each mapping quality value. Mapping quality reflects the confidence of read alignment, typically ranging from 0 to 60.

        Created with MultiQC

        Insert Size Distribution

        This histogram displays the distribution of insert sizes (distance between paired-end reads). A typical insert size distribution should show a smooth peak.

        Created with MultiQC

        Mapped Reads Clipping Profile

        Shows the percentage of clipped bases at each read position. Clipping (hard or soft) is inferred from the CIGAR string in the BAM file and may indicate sequencing or alignment artifacts.

        Created with MultiQC

        Mapped Reads Nucleotide Content

        Displays the proportion of each nucleotide (A, C, G, T) at each read position. Unbalanced content could indicate biases in sequencing or library preparation.

        Created with MultiQC

        Homopolymer Indels Distribution

        This bar plot shows the number of insertions or deletions (indels) found within homopolymer regions (e.g., stretches of AAAAA) and non-homopolymer regions. High numbers may suggest sequencing issues.

        Created with MultiQC

        Genome Fraction Coverage

        Shows the percentage of the reference genome covered at or above different coverage thresholds. For example, 80% at 25X means 80% of the genome is covered by at least 25 reads.

        Created with MultiQC

        RSeQC

        Evaluates high throughput RNA-seq data.URL: http://rseqc.sourceforge.netDOI: 10.1093/bioinformatics/bts356

        Read Distribution

        Read Distribution calculates how mapped reads are distributed over genome features. In RNA-seq, typically >70% of reads map to exons, reflecting mature, properly spliced transcripts. A high proportion of intronic or intergenic reads may indicate sample quality issues, contamination, or incomplete splicing. Other sequencing strategies do not rely on these distributions for QC. For instance, WGS typically shows ~1–2% of reads in CDS exons, <1% in 5’ UTRs, ~30–40% in introns, <0.1% in TSS/TES, and ~50–60% intergenic; while WXS often has ~60–80% in CDS exons, <10% in 5’ UTRs, and generally <5% in introns, TSS/TES, or intergenic regions. Always interpret these metrics within the context of the chosen protocol and its expected outcomes.

        Created with MultiQC